When it comes to machine learning, a lot of the attention in the past six years has focused on the training of neural networks and how the GPU accelerator radically improved the accuracy of networks, thanks to its large memory bandwidth and parallel compute capacity relative to CPUs. …
It doesn’t take a machine learning algorithm to predict that server makers are trying to cash in on the machine learning revolution at the major nexus points on the global Internet. …
A research team from Nvidia has provided interesting insight about using mixed precision on deep learning training across very large training sets and how performance and scalability are affected by working with a batch size of 32,000 using recurrent neural networks. …
The Texas Advanced Computer Center (TACC) will house the latest leadership-class supercomputer funded by the National Science Foundation, a project that stands as a tribute to the NSF’s continued efforts to push supercomputing projects and the latest indication of the ground the organization is losing to the Department of Energy (DOE) in this effort. …
If there is anything the hyperscalers have taught us, it is the value of homogeneity and scale in an enterprise. …
Given the rollout of the “ZZ” and “Boston” variants of its Power9 systems, which are aimed at customers who are building clusters and at midrange enterprises that use a Power System server as their main back-end system, you might be expecting for the Power Systems line at IBM to have had a big bump in the second quarter of this year. …
Back in the late 1970s and early 1980s, big iron in datacenters had to have water cooling, which was a pain in the neck in terms of the system and facilities engineering. …
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